Population burst propagation across interacting areas of the brain

Author:

Chen Yu12ORCID,Douglas Hannah3ORCID,Medina Bryan J.4,Olarinre Motolani13,Siegle Joshua H.5ORCID,Kass Robert E.123ORCID

Affiliation:

1. Machine Learning Department, Carnegie Mellon University, Pittsburgh, Pennsylvania

2. Neuroscience Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania

3. Department of Statistics & Data Science, Carnegie Mellon University, Pittsburgh, Pennsylvania

4. Department of Computer Science, University of Central Florida, Orlando, Florida

5. MindScope Program, Allen Institute, Seattle, Washington

Abstract

We developed a novel statistical method for identifying coordinated propagation of activity across populations of spiking neurons, with high temporal accuracy. Using simultaneous recordings from three visual areas we document precise timing relationships on a trial-by-trial basis, and we show how previously existing techniques can fail to discover coordinated activity in cases where the new approach finds very strong cross-area correlation.

Funder

HHS | NIH | National Institute of Mental Health

HHS | NIH | National Institute on Drug Abuse

Publisher

American Physiological Society

Subject

Physiology,General Neuroscience

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